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  • 學位論文

三維天車系統之適應模糊滑動影像追蹤控制方法

An Image Tracking Method with Adaptive Fuzzy Sliding Mode Control for a Three Dimensional Overhead Crane System

指導教授 : 張政元

摘要


本論文探討傳統三維天車系統的硬體問題與控制方法,並利用影像技術取代傳統編碼器,做為系統回授資訊的來源,以提供天車系統控制器做為輸入資訊。文中探討編碼器在天車系統上使用時存在的弊病(機械震動、搖擺偵測不真實等),並以實驗室的實際三維天車系統模型為例,從影像中獲取三維空間之天車系統的相關資訊。 透過對天車系統機構的觀察,選取/給予適當的影像特徵,並利用最亮點做為快速追蹤的主要方式;另外使用了可移動之追蹤框降低運算量,使系統能夠達到即時控制的目的。免模型的天車系統控制器使用了抗干擾能力強的滑動模式控制,並配合模糊邏輯的使用,使得滑動平面之斜率可以適應於系統不同的狀態,並提升了控制性能。 本論文結合了影像追蹤與智慧型天車系統控制器,成為一個具有快速定位、抑制搖擺,並擺脫編碼器弊病的三維影像天車系統控制器。文中以實際三維天車系統模型實驗,比較傳統手動操作方式、編碼器回授之自動控制方式與影像回授之自動控制方式間的優劣與差異,並針對實驗結果加以探討、建議與總結。

並列摘要


An image tracking method for a three dimensional overhead crane system was proposed in this thesis. Some mechanism issues and control methods were discussed, which aim at settling defects of encoders using in overhead crane system. Image took the place of encoders in the overhead crane system as a source of feedback for crane controller. The state of the overhead crane system was acquired from images, e.g. positions of the cart, load swing angles and the rope length. A real three dimensional overhead crane system model in the lab was used to to testify to the ability in a real-time control of the crane system and the real-time info-retrieval from images. Observation was used for mechanism of overhead crane system by way of select/give image features, and using the brightest point as the main tracking method; to reduce the computation with moving tracking areas to achieve the objective of control the whole system in real-time. For the model-free crane controller, the sliding mode control was used with fuzzy logic, therefore the slope of sliding function could adapt to the system's different states and improve the performance of control. Methods developed in this thesis give the ability of an overhead crane controller in position, anti-swing, and further, with no drawbacks to encoders. Part of paragraph was used to compare with manual operated control, encoder feedback with intelligent control and visual feedback with intelligent control. In the end, suggestions were made for further research.

參考文獻


[1] B. Ma, Y. Fang, and Y. Zhang, “Switching-based emergency braking control for an overhead crane system,” IET Control Theory & Applications, vol. 4, no. 9, pp. 1739–1747, 2010.
[2] N. Sun, Y.-C. Fang, P.-C. Wang, and X.-B. Zhang, “Adaptive trajectory tracking control of underactuated 3-dimensional overhead crane systems,” ACTA Automatica Sinica, vol. 36, no. 9, pp. 1287–1294, 2010.
[3] A. Burananda, J. Ngamwiwit, S. Panaudomsup, T. Benjanarasuth, and N. Komine, “Neural network based self-tuning control for overhead crane systems,” in Proceedings of the 41st SICE Annual Conference. SICE 2002., 2002, vol. 3, pp. 1944–1947.
[4] C.-Y. Chang and K.-H. Chiang, “Fuzzy projection control law and its application to the overhead crane,” Mechatronics, vol. 18, no. 10, pp. 607–615, 2008.
[5] H.-H. Lee and S.-K. Cho, “A new fuzzy-logic anti-swing control for industrial three-dimensional overhead cranes,” in Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation, 2001, vol. 3, no. 7, pp. 2956–2961.

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